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Novel capacitive proximity sensors for assessing the aging of composite insulators
Sensors and Actuators A 253 (2017) 75–84
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Novel capacitive proximity sensors for assessing the aging of composite insulators Jingpin Jiao ∗ , Liang Li, Bin Wu, Cunfu He College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China
a r t i c l e
i n f o
Article history: Received 2 September 2016 Received in revised form 31 October 2016 Accepted 18 November 2016 Available online 21 November 2016 Keywords: Composite insulator Capacitive proximity sensor Penetration depth Aging Non-destructive testing Silicone rubber sheds
a b s t r a c t A novel electrode structure consisting of a variable spacing interdigital electrode (VS-IDE) was proposed for assessing of the aging of silicone rubber sheds with variable thickness. A series of numerical simulations and experiments have been carried out to investigate the influences of finger number, unit width, and metallization ratio on the signal strength and penetration depth of sensors with a traditional interdigital electrode structure. According to the relationship between the penetration depth and the unit width, the width of each finger that composed the VS-IDE structure sensor was optimized individually to confine the electric field line within the sheds under test. Experimental results showed that compared to the other sensors, the optimal sensor exhibited high amplitude, high sensitivity, and excellent stability against the effects of environmental humidity. The developed capacitive proximity sensors have been used for assessing of the aging of silicone rubber sheds in composite insulators, and the feasibility of assessing insulation degradation by quantitative capacitive techniques is demonstrated. © 2016 Elsevier B.V. All rights reserved.
1. Introduction In recent years, composite insulators (silicone rubber insulators) have been widely used in power transmission systems because of their excellent attributes, such as being lightweight and high in mechanical strength, and offering excellent resistance to pollution and vandalism. However, the superior performance of composite insulators degrades over time because of high-voltage surge and unfavorable environmental factors, such as high temperatures, pollution, humidity, ultraviolet (UV) radiation, and oxidation. Aging of the composite insulators will lead to electrical property degradation or deterioration of the external insulation, threatening the safety and reliability of the power supply. A composite insulator consists of a glass fiber-reinforced polymer rod attached with metal end fittings and silicone rubber sheds which cover the rod (as shown in Fig. 1). The silicone rubber sheds are molded into a series of concentric disks to protect the rod from the environment and provide a sufficiently long leakage current path. Because of lengthy direct exposure to a harsh environment, aging is more likely to occur in silicone rubber sheds. It has been reported that the failures due to the aging of silicone rubber sheds in composite insulators have always been a challenge in engineer-
∗ Corresponding author. E-mail address: [email protected] (J. Jiao). http://dx.doi.org/10.1016/j.sna.2016.11.025 0924-4247/© 2016 Elsevier B.V. All rights reserved.
ing practice [1,2]. Therefore, it is critically important to detect the deterioration of silicone rubber sheds. Several methods have been proposed to estimate the aging of silicone rubber insulators [2,3]. These methods include visual inspection [4], UV imaging method [5,6], infrared ray imaging [7], ultrasonic non-destructive testing [8,9], hydrophobicity classification [10], nuclear magnetic resonance (NMR) [11], electric field measurement method [12], and leakage current measurement [13]. Extensive research has been conducted on assessment of aging of insulators using above methods; however, it has been found that these methods have limitations in measurement precision, reliability, and engineering practicality [14,15]. For capacitive sensing techniques the most common electrode structures are the planar parallel plate electrodes and the co-planar electrodes (called capacitive proximity sensors). The working principle of capacitive proximity sensors are based on the fringing effect of the electric field. Compared to the traditional parallelplate capacitor, capacitive proximity sensors have unique features, such as one-side access (the other side can be open to the ambient), easy control of signal strength by changing its dimensions, multiple physical effects in the same structure (electric, magnetic, acoustic), and a wide frequency spectrum of use. Therefore, they have been widely used in many fields, such as material property monitoring, humidity sensing, electrical insulation properties sensing, chemical sensing, and bio-sensing.
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Fig. 1. Structure of composite insulator. Fig. 3. Fundamental parameters of interdigitated electrode structure.
Fig. 2. 3D model of the composite insulator and the cross-sectional drawing of silicone rubber shed.
Capacitive proximity sensing techniques have been widely used for nondestructive evaluation (NDE) of low-conductivity materials [16–21]. Based on detecting the local variation of the dielectric properties of materials under testing, capacitive sensing techniques have been used for structure-healthy monitoring (SHM) of the concrete slab retrofitted with composites [18,19]. EI-Dakhakhn et al. [20] applied the proximity capacitive technique for unfilled cells detection in grouted masonry constructions. A concentric coplanar capacitive sensor was developed for the quantitative characterization of material properties for multi-layered dielectrics [21], and the effectiveness of the proposed method for water intrusion detection in random structures was experimentally validated. The outside insulation layer of the electric cables is also typically low-conductivity material. Research has applied capacitive sensing techniques to characterize cable insulation properties. Chen and Bowler [22] designed a capacitive probe for evaluation of wiring insulation permittivity, and experiments demonstrated the feasibility of assessing wiring insulation degradation status by quantitative capacitive techniques. Proximity-coupled interdigital sensors are introduced to detect insulation damage in power system cables, and the measurement results confirm that the proximity capacitive technique is sensitive to the presence of holes and water trees in a power line cable [23]. To detect aircraft wire aging damage, Sheldon and Bowler [24] developed an interdigital capacitive sensor and experimentally verified the capacitance variation resulted from aircraft fluid immersion. Research indicates that the patterns and parameters of electrodes have great influence on capacitive sensor performances, such as signal strength, penetration depth, sensitivity, and noise-tosignal ratio, all of which affect the detecting capability of capacitive proximity sensors. Many efforts have been devoted to improving the performance of capacitive proximity sensors [25–27]. Several sensor patterns including square-shaped, maze, spiral, and comb patterns were investigated, and it was demonstrated that complex sensor patterns can increase the effective electrode area and then improve sensor signal and sensitivity [25]. To improve signal strength and sensitivity, Rivadeneyra et al. [28] designed a serpentine structure which is a combination of meandering and interdigitated electrodes. A capacitive sensor of interdigital elec-
Fig. 4. 2D finite element model of proximity interdigital sensor.
trode structure with increased height was fabricated for humidity measurement [29]. Compared to the traditional interdigital electrode sensor, the proposed sensor showed higher sensitivity owe to the horizontal electric field lines confined in the polyimide sensing layer. Syaifudin et al. [30,31] investigated the influence of electrode configuration on performance of capacitive proximity sensors and found that the optimal number of negative electrodes between two adjacent positive electrodes can improve the sensitivity for chemical detection. For water detection in an automatic windshield system, a few petal-like electrode structures were designed [32]. The silicone rubber sheds are made of high-temperature vulcanization silicone rubber (HTVSR), a typical dielectric material [33]. Aged silicone rubber may lead to fracture of the molecular chains and produce large numbers of free radicals, changing the permittivity (dielectric constant). Capacitive sensing, however, is ideally suited for characterization of dielectric materials due to the closely relationship between the measured capacitance and the relative permittivity (dielectric constant) of the material. To ensure the self-cleaning ability of the composite insulators under contaminated conditions, the umbrella skirt structure is designed to be an inclined plane with a certain angle, whose thickness decreases gradually from near the fiberglass-reinforced resin rod to the edge of the umbrella skirt. In this paper, the capacitive proximity sensing method is applied to assess the insulation degradation of silicone rubber sheds in a composite insulator. The influence of finger number, unit width, and metallization ratio on the performance of capacitive proximity sensors was investigated by simulation and experiments. Capacitive proximity sensors with variable spacing interdigital electrode (VS-IDE) structure were designed for nondestructive testing of thickness gradient samples. The proposed sensors are experimentally measured and used to assess the aging of silicone rubber sheds in a composite insulator.
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η=0.1 η=0.2 η=0.3 η=0.4 η=0.5 η=0.6 η=0.7 η=0.8 η=0.9
5 Capacitance C/ F
60
x 10
4 3 2 1
40 30 20 10 0
0
2
η=0.1 η=0.2 η=0.3 η=0.4 η=0.5 η=0.6 η=0.7 η=0.8 η=0.9
50 Relative capacitance /%
6
77
2
4
4 6 8 10 12 14 Thickness of test samples h/mm (a) Absolute capacitance
6 8 10 12 14 Thickness of test samples h/ mm (b) Relative capacitance
Fig. 5. Capacitance obtained from simulations when the finger number of sensor is 4.
2. Capacitive sensor design and optimization Fig. 2 shows the 3D model of the detected composite insulator, FXBW4-110/100-B, and the cross-sectional drawing of silicone rubber shed (umbrella skirt). The outer and inner radii of the umbrella skirt are 59 mm and 13 mm, respectively. The thickness of umbrella skirt decreases gradually from 6.27 mm near the core rode to 2.33 mm at the outer edge. The angle of the top and bottom surfaces is about 5◦ . For the convenience of sensor installation, a limited region near the core rode and at the outer edge is reserved. Consequently, 38 mm in the radial direction can be used for the arrangement of electrodes. In this region, the thickness of umbrella skirt decreases gradually from 5.89 to 2.0 mm. Owing to the high signal strength and sensitivity, the interdigitated electrode structure has been widely used in capacitive proximity sensing. The fundamental parameters of interdigitated electrode structure are illustrated in Fig. 3, including mainly the number of fingers n, unit width of each finger w, and spacing between two adjacent fingers g. Here, a new parameter C, named width of a basic interdigital unit, is defined. Obviously, the value of C equals the sum of finger width w and finger spacing g. Likewise, the metallization ratio Á is equal to the ratio of the finger width w to the basic interdigital unit width C, = w/(w + g). L is the length of the interdigitated electrode structure, which is specified as 38 mm in this paper. 2.1. Numerical simulation of proximity interdigital sensors The effect of the electrode parameters (finger number, metallization ratio) on the performance of proximity interdigital sensors was investigated by numerical simulations. An FEM (finite element method) numerical model of the proximity interdigital sensor was developed, and electrostatic simulations were performed in Comsol Multiphysics 4.4 software. Fig. 4 shows a typical 2D finite element model of proximity interdigital sensor with 4 fingers, consisting of driving electrodes, sensing electrodes, substrate for supporting the electrodes, shielding layer, and the materials under test. The surrounding of model is full of air. The test sample is high-temperature vulcanized silicone rubber (HTVSR) with relative dielectric permittivity 5.6, and the substrate is polymethyl methacrylate with a thickness of 2.5 mm and relative dielectric permittivity of 4.2. The thickness of the copper electrode is 0.1 mm. The driving electrode is set to 5 V and all other electrodes are set to 0 V, a Dirichlet boundary condition in nature. Based on the above model, simulations were first performed to investigate the effect of the metallization ratio on the measured capacitance at samples with different thickness. In these
simulations, the metallization ratio varies from 0.1 to 0.9 with an increment of 0.1; and the thickness of test samples varies from 2 to 15 mm with an increment of 1 mm. In this section the length of the electrode structure is constant (38 mm). According to the geometric relations of interdigitated electrode structure, the finger width and spacing in each model can be determined as follows: w=
∗L n
(1)
g=
(1 − ) ∗ L n−1
(2)
According to the simulated result, the inter-electrode capacitance can be calculated using C=
1 1 Dd˝ = ε0 εr ∇ ˚d˝, V˝ V˝
(3)
where is the electrode-covered area in models, D is the electric displacement vector, and V is the potential difference between the driving and sensing electrodes. Fig. 5(a) shows the capacitance values obtained from the simulations when the finger number is 4. It can be seen that the metallization ratio and thickness of test sample affects the measured capacitance value. When the thickness of test samples is identical, the capacitance values increase with the increasing of the metallization ratio; moreover, the capacitance values from different metallization ratios exhibit similar trends with respect to the thickness of test samples. That is, the capacitance increases slightly in proportion to the thickness of test samples and then reaches certain stable values. One explanation for this is that along with the increase of metallization ratio comes an increase in effective area of electrodes, which lead to the increasing the capacitance with metallization ratio; as the thickness of test samples becomes thicker, more electric field lines pass through the test samples and reach the sensing electrodes, which lead to an increase in capacitance values. However, the capacitance will be stabilized at certain values once the thickness of the test sample reaches the specific penetration depths. Penetration depth is a measure of evaluating the ability of electric field intensity penetrating through the test samples. Until now, no strict definition of penetration depth for capacitive proximity sensors has existed. One way to evaluate the penetration depth is according to the distribution of the relative capacitance ıC, which can be represented as ıC =
|C − Cs | × 100%, Cs
(4)
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Fig. 6. Distribution of electric field lines when metallization ratio varied from 0.1 to 0.9, respectively.
where Cs is the stable capacitance at the same metallization ratio. The effective penetration depth corresponds to the position where the relative capacitance equals 10%. The relative capacitance and penetration depth corresponding to Fig. 5(a) are shown in Fig. 5(b). It can be seen that the penetration depth decreases as the metallization ratio increases. A possible explanation is that the increasing of metallization ratio results in a decreasing of finger spacing, which is closely related to the penetration depth. The effect of metallization ratio on penetration depth can also be vividly illustrated by the distribution of the electric field in space. Fig. 6 shows the distribution of electric field lines when the metallization ratio of electrodes varies from 0.1 to 0.9, the finger number is 4, and the thickness of samples is identical. It can be seen that with the increase of metallization ratio, there were less electric field lines which can penetrate the test samples and escape to the air. Though the distribution of electric field lines cannot use for quantitative description of penetration depth, the results support above conclusions that along with the increase of metallization ratios comes a decrease in penetration depths and an increase in capacitance value. Similarly, numerical simulation analysis was carried out for the influence of metallization ratio on the performance of proximity interdigital sensors with different number of fingers. According to the numerical simulation, the dependencies of the penetration depth versus the metallization ratio for proximity interdigital sensors with different number of fingers are depicted in Fig. 7. The finger number and metallization ratio obviously greatly affect the penetration depth of proximity interdigital sensors. Along with the increase of finger number comes an obvious decrease in penetration depth. For proximity interdigital sensors with identical finger number, the penetration depth decreases with the increasing of metallization ratio, which is consistent with above results.
Fig. 7. Penetration depth versus metallization ratio for proximity interdigital sensors with different number of fingers.
The penetration depth curves shown in Fig. 7 are particularly useful for the structure parameter in designing of proximity interdigital sensors. According to the thickness distribution range of the umbrella skirt (2–5.89 mm), the basic parameters of proximity interdigital sensors, such as finger number, width of basic interdigital unit, and metallization ratio, can be determined. The penetration depth may reach up to 6 mm when the metallization ratio is less than 0.4 for proximity interdigital sensors with 4 fingers. At this case the width of a basic interdigital unit C is 9.5 mm; the penetration depth may reach up to 2 mm when the metallization ratio is less than 0.5 for proximity interdigital sensors with 8 fingers. In this case the width of a basic interdigital unit C is 4.75 mm. Therefore,
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45
C10-η0.5 C9-η0.5 C8-η0.5 C7-η0.5 C6-η0.5 C5-η0.5 C4-η0.5
Relative capacitance d /%
40 35 30 25 20 15 10 5 Fig. 8. 2D simulation model for proximity interdigital sensors with single unit.
0 x 10
2
-12
1.4
6 8 10 12 14 Thickness of test samples
Fig. 10. Relative capacitance value versus thickness of test samples for proximity interdigital sensor with single unit.
1.3 Capacitance /F
4
1.2 1.1 C10-η0.5 C9-η0.5 C8-η0.5 C7-η0.5 C6-η0.5 C5-η0.5 C4-η0.5
1 0.9 0.8 0.7 2
4
6
8
10
12
14
Thickness of test samples h/mm Fig. 9. Capacitance value versus thickness of test samples for proximity interdigital sensor with single unit.
in following research, the width of a basic interdigital unit ranges from 4 to 10 mm. 2.2. Numerical simulation of proximity interdigital sensors with single unit A 2D numerical simulation model was established as shown in Fig. 8, and simulations were carried on proximity interdigital sensors with a single unit, in which the width of a basic interdigital unit ranged from 4 to 10 mm. The influences of basic interdigital unit width and test sample thickness on the performance of proximity interdigital sensors with a single unit were investigated through simulation. In simulation models, the metallization ratio was set to 0.5, and the other parameters were the same as those described in Section 2.1. Figs. 9 and 10 give the results of the simulations. It can be seen that the variations of capacitance and its relative value with thickness of test samples closely resemble that obtained from sensors with multiple fingers (as shown in Fig. 5). In addition, as can be seen from the capacitance values in Fig. 9, the width of the basic interdigital unit greatly affects the measured capacitance value. When the thickness of test samples is identical, the capacitance values decrease with the increasing of width of a basic interdigital unit. However, as seen from Fig. 10, for interdigital sensors with a single unit the penetration depth increases with the increasing of unit width. Similarly, numerical simulation was carried out for the influence of unit width on the performance of proximity interdigital
Fig. 11. Penetration depth versus metallization ratio for proximity interdigital sensors with different unit width.
sensors with different metallization ratio. According to the results of numerical simulation, the dependencies of the penetration depth versus the metallization ratio for proximity interdigital sensors with different unit width are depicted in Fig. 11. As expected, unit width and metallization ratio obviously greatly affect the penetration depth of proximity interdigital sensors. Along with the increase of unit width comes an obvious increase in penetration depth. An explanation for this is that along with the increase of unit width (metallization ratio is constant) comes an increase in effective area of electrodes, which lead to the increasing of capacitance values with unit width. Meanwhile, the variations of penetration depth versus metallization ratio exhibited similar behavior for proximity interdigital sensors with different unit width. When the metallization ratio is less than 0.4, the penetration depth slowly increases with metallization ratio; when the metallization ratio is within the range of 0.4–0.7, the penetration depth is almost constant; and when the metallization ratio is greater than 0.7, the penetration depth slowly decreases with metallization ratio. The finger number and metallization ratio obviously greatly affect the penetration depth of proximity interdigital sensors. Along with the increase of finger number comes an obvious decrease in penetration depth. For proximity interdigital sensors with identical finger number, the penetration depth decreases with the increasing of metallization ratio, which is consistent with above results.
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Table 1 Parameters for different proximity interdigital capacitive sensors (unit: mm). Sensor Number
Interdigital unit C1
Sensor-1# Sensor-2# Sensor-3# Sensor-4#
C2
C3
C4
C5
C6
w1
g1
w2
g2
w3
g3
w4
g4
w5
g5
w6
3.8 5 6 7
7.6 5 4 3
3.8 5 5 5.6
7.6 4 3.2 2.4
3.8 4 4.8 4.9
7.6 3 2.4 2.1
3.8 3 3.6 4.2
– 2.5 2 1.8
– 2.5 3 3.5
– 2 1.6 1.5
– 2 2.4 2
Fig. 12. Schematic diagram of VS-IDE capacitive sensor. Fig. 13. Electrode arrangement of VS-IDE capacitive sensor.
The relationship of penetration depth and metallization ratio under different unit width provides guidelines for the design of proximity interdigital sensors used in test samples with different thickness.
Table 2 Comparison of the capacitance for different sensors at different environmental humidity. Capacitance (pF)
2.3. Optimization of proximity interdigital sensors Considering the gradually varying thickness of silicone rubber sheds, the width and metallization ratio of each interdigital unit composed of proximity interdigital sensors were optimized individually. The optimization was to obtain high amplitude and high sensitivity under the condition that the penetration depth was ensured. In pursuance of the above guidelines, a novel capacitive proximity interdigital sensor consisting of VS-IDE structure has been developed for nondestructive testing of silicone rubber sheds with gradually varying thickness. Fig. 12 shows the schematic diagram of a VS-IDE capacitive sensor, which consists of driving electrode (1), sensing electrode (2), substrate (3), guarding electrode (4), and lead connector (5). The driving electrode and the sensing electrode are deposited on a PMMA (polymethyl methacrylate) substrate, while the guarding electrode is deposited on the opposite side of the substrate to protect the sensor. The lead connector is welded on the guarding plane to provide a reliable connect for the sensor and experimental equipment. The middle pins of the SMB connectors are respectively connected to the driving electrode and the sensing electrode through the pre-reserved holes on the substrate. Both the driving and sensing electrodes consist of several interdigital fingers, which are arranged alternately in sequence, and the width and metallization ratio for each interdigital unit is determined by the local thickness of the test sample. The arrangement of electrodes is shown in Fig. 13. As mentioned in Section 2, in the radial direction of the umbrella skirt the width that can be used for the arrangement of electrodes is 38 mm, and thickness ranges from 5.89 to 2.0 mm. In accordance with the requirement of penetration depth shown in Fig. 11, only the interdigital units, whose width is 10 mm, and the metallization ratio (0.5, 0.6, or 0.7) satisfied the penetration depth criteria of 5.83 mm. Therefore, 3 VS-IDE capacitive sensors are obtained on condition that the total width of the electrode is identical. Table 2
no water film 0.5-mm thick water film capacitance variation relative capacitance change rate
Sensor number 1#
2#
3#
4#
1.047 1.560 0.513 48.95%
4.151 4.641 0.490 11.81%
4.919 5.427 0.507 10.31%
5.875 6.433 0.5688 9.51%
Fig. 14. Finite element model for designed sensors.
provides details of the capacitive sensors, including a traditional proximity interdigital sensor with 4 fingers. Since it has an equal spacing interdigital electrode, it is named ES-IDE capacitive sensor (Sensor-1#). Similarly, performance of 4 sensors was studied with numerical simulations. Fig. 14 shows the finite element model for the designed sensors. Fig. 15 shows the electric field line distribution of the sensors. Compared to the distribution of electric field lines for the ES-IDE capacitive sensor, the electric field lines of VS-IDE capacitive sensors are mostly confined within the test samples. In particular, the electric field lines are further confined in the test sample for sensor4#. The capacitance value of 4 sensors are, respectively, 1.05pF, 4.15pF, 5.12pF, and 5.87pF. Fig. 16 shows the capacitance value versus relative dielectric constant of the test sample. It can be seen that compared to the ES-IDE capacitive sensor, the proposed VS-IDE capacitive sensors perform better in signal amplitude and mea-
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Fig. 15. Electric field line distribution for different sensors: (a) Sensor-1#, (b) Sensor-2#, (c) Sensor-3#, (d) Sensor-4#.
Capacitance /F
-12
9 8 7 6 5 4 3 2 1 0
x 10
Fig. 17. Schematic of experimental system for capacitance measurement.
1# 2# 3# 4#
2
3
4
5
6
7
8
Relative dielectric constant Fig. 16. Capacitance value versus relative dielectric constant of test samples using different sensors.
surement sensitivity. Furthermore, compared to the other 2 VS-IDE capacitive sensors, sensor-4# has optimal performance. Another advantage of the proposed VS-IDE capacitive sensors is that they are less affected by environmental factors, such as humidity. To investigate the effect of environmental humidity on the performance of the above sensors, a thin layer of water with thickness of 0.5 mm was introduced in the simulation model shown in Fig. 14. Table 2 shows the simulated results and capacitance variations due to the presence of the water layer. The water layer has different effect on the capacitance of different sensors. It has a significant effect on the capacitance of ES-IDE capacitive sensor, and its relative change rate of capacitance is nearly 48.95%; however, it has a slight effect on the capacitance of VS-IDE capacitive sensors. In particular, it has minimal influence on the performance of sensor-4#. Therefore, simulation demonstrates that the proposed VS-IDE capacitive sensors exhibited excellent performance in signal amplitude, sensitivity, and stability against the effects of environmental humidity. 3. Performance testing of capacitive proximity sensors Benchmark capacitive experiments were carried out to test the performance of the capacitive proximity sensors. The schematic of experimental system is shown in Fig. 17. 4294A Precision Impedance Analyzer (Agilent) is the core component of the capacitive measurement system. The test samples are made of HTVSR, and their geometry is identical to those in the simulations above. A special jig is used to keep contact tight between the capacitive sensor and the test sample. Fig. 18 shows the measured capacitance of the proximity interdigital capacitive sensors described in Table 1. It is noted that the experimental and simulation results of different proximity
Fig. 18. Measured capacitance of the proximity interdigital capacitive sensors.
Table 3 Comparison of the measured capacitance for different sensors at different environmental humidity. Capacitance (pF)
no water film with water film capacitance variation relative capacitance change (%)
Sensor number 1#
2#
3#
4#
1.411 1.560 0.149 10.53
3.340 3.432 0.092 2.75
3.894 3.952 0.045 1.48
4.579 4.602 0.016 0.51
interdigital capacitive sensors have essentially the same changing tendency. Experiments demonstrate that compared to the ES-IDE capacitive sensor, the proposed VS-IDE capacitive sensors have a better performance in signal amplitude. Additionally, experiments were conducted to verify the environmental stability of the VS-IDE capacitive sensors. In these experiments a thin layer of water was coated on the test samples; the other arrangement was identical to experiments above. Table 3 compares the measured capacitance for different sensors at different environmental humidity. Clearly, the experimental results agree with the above simulation results. Experiments demonstrate that the water layer has a slight effect on the capacitance of VSIDE capacitive sensors. The relative capacitance variation ratio of sensor-4# is the lowest at only 0.51%. In summary, experiments demonstrate that the proposed VSIDE capacitive sensors exhibited excellent performance in signal amplitude, sensitivity, and stability against the effects of environmental humidity. Besides, among 3 kinds of VS-IDE capacitive sensors, the performance of sensor #4 is the best one.
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-11
1.2
x 10
Capacitance C / F
0h
1
10h 20h
0.8
40h 60h
0.6 0.4 0.2 0 1#
2# 3# Sensor number
4#
Fig. 19. Annular capacitive proximity sensors. Fig. 22. Measured capacitance from umbrella sheds with varying degrees of aging.
in Table 1. The sensors were fabricated using printed circuit board technology as shown in Fig. 19. Fig. 20 shows the experimental system for the aging detection of silicone rubber sheds. Similar to the rectangle jig in Fig. 17, an annular jig keeps contact tight between the capacitive sensor and the sheds. 4294A Precision Impedance Analyzer (Agilent) is used for capacitance measurement. The tested composite insulators, FXBW4-110/100-B, were soaked in sulfuric acid (concentration of 70%) at different immersion periods to accelerate different degrees of aging. Fig. 21 shows the typical unaged and aged umbrella sheds. A thin layer of age coating can be seen to have formed on the surface of the aged shed layer, which exhibits the phenomenon of chalking and whitening. In addition, visible micro-cracks appear on the surface when the shed is bent slightly. 4.2. Results and discussion Fig. 20. Experimental setup for aging detection of silicone rubber sheds.
4. Experiments of aging detection of silicone rubber sheds In this section, the capacitive proximity sensing method is applied to assess the insulation degradation of silicone rubber sheds in a composite insulator. 4.1. Experimental system Four kinds of annular capacitive proximity sensors were designed for the aging detection of silicone rubber sheds (shown in Fig. 1). The structural parameters of sensors, such as finger number, unit width, and metallization ratio, are identical with those
Experiments of capacitance measurement were conducted on umbrella sheds with varying degrees of aging using the designed annular capacitive proximity sensors. Fig. 22 shows the typical results. For each case, the experiment was repeated 6 times, and the error bars represent the standard deviation of these measurements. The measured capacitance values can be seen to have decreased with the increase of the immersion period for the same sensor, and the capacitance measured by the VS-IDE capacitive sensors is significantly higher than that of the ES-IDE capacitive sensor. Among 3 VS-IDE capacitive sensors, sensor-4# performs best in signal amplitude in any case. Fig. 23 gives the measured capacitance variations versus the immersion period. The immersion period obviously greatly affects the measured capacitance value, and the capacitance variations from different sensors exhibit similar trends with respect to the
Fig. 21. Comparison of the different test specimen.
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-12
Capacitance variation C / F
2
x 10
1.5
1
Sensor-1# Sensor-2# Sensor-3# Sensor-4#
0.5 0
10
20
30 40 50 Immersion time t/ h
60
Fig. 23. Measured capacitance variation versus immersion period.
immersion period. That is, the capacitance variation increases slightly in proportion to the immersion period and then reaches certain stable values. Additionally, under the same immersion period, the capacitance variation measured by the annular VSIDE capacitive sensors was significantly higher than that of the ES-IDE capacitive sensor. Among the 3 VS-IDE capacitive sensors, sensor-4# has the highest measurement sensitivity. Therefore, the capacitive proximity sensing method can be used for evaluation of the aging of the umbrella shed in composite insulators, and the VS-IDE capacitive sensor is more sensitive to the aging of umbrella sheds. 5. Conclusion The potential of the capacitive proximity sensing technique for the aging detection of umbrella shed in composite insulators was investigated. Numerical simulations have been carried out to analyze the influences of finger number, unit width, and metallization ratio on the signal strength and penetration depth of sensors with traditional interdigital electrode structure. Considering the gradually varying thickness of silicone rubber sheds, the width and metallization ratio of each interdigital unit composed of the proximity interdigital sensors were optimized individually to confine the electric field line within the sheds being tested. A novel electrode structure consisting of a VS-IDE was proposed for assessing of the aging of silicone rubber sheds with variable thickness. Experiments demonstrated that the proposed VS-IDE capacitive sensors exhibited excellent performance in signal amplitude, sensitivity, and stability against the effects of environmental humidity. The developed capacitive proximity sensors have been used for assessing of the aging of silicone rubber sheds in composite insulators. Experimental results demonstrated that the capacitive proximity sensing method can quantitatively evaluate the aging of umbrella shed in composite insulators, and compared to the ES-IDE capacitive sensor the VS-IDE capacitive sensor is more sensitive to aging of umbrella sheds. Acknowledgements The study was supported by the National Natural Science Foundation of China (Grant nos. 11272017, 11572010); the National Key Research and Development Program of China (2016YFF0203002). References [1] N. Yoshimura, S. Kumagai, S. Nishimura, Electrical environmental aging of silicone rubber used in outdoor insulation, IEEE Trans. Dielectr. Electr. Insul. 6 (5) (1999) 632–650.
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[2] A. Shimada, M. Sugimoto, H. Kudoh, et al., Degradation mechanisms of silicone rubber (SiR) by accelerated ageing for cables of nuclear power plant, IEEE Trans. Dielectr. Electr. Insul. 21 (1) (2014) 16–23. [3] B. Lutz, L. Cheng, Z. Guan, et al., Analysis of a fractured 500 kV composite insulator-identification of aging mechanisms and their causes, IEEE Trans. Dielectr. Electr. Insul. 19 (5) (2012) 1723–1731. [4] S.M. Gubanski, A. Dernfalk, J. Andersson, H. Hillborg, Diagnostic methods for outdoor polymeric insulations, IEEE Trans. Dielectr. Electr. Insul. 14 (5) (2007) 1065–1079. [5] B. Pinnangudi, R.S. Gorur, A.J. Kroese, Quantification of corona discharges on nonceramic insulators, IEEE Trans. Dielectr. Electr. Insul. 12 (3) (2005) 513–523. [6] Lei Hongcai, Zang Chunyan, Jiang Zhenglong, et al., Detecting breakage defect of post insulator with ultraviolet imaging method, High Volt. Appar. 45 (5) (2016) 87–92. [7] E. Spangenberg, G. Riquel, In service diagnostic of composite insulators EDF’s test results, Montreal, Quebec, in: Proc. 10th Int. Symp. on HV Eng. Canada, 4, 1997, pp. 139–142 (3). [8] D.W. Auckland, C.D. Smith, B.R. Varlow, Ultrasound-a diagnostic tool for NDT of insulation degradation, Dielectric Materials, Measurements and Applications, Sixth International Conference on IET (1992) 115–118. [9] Xie Congzhen, He Zilan, Ling Yongxing, et al., Using ultrasonic phased array to inspect the internal defects of composite insulators, Proc. CSEE 32 (Suppl) (2012) 63–68. [10] T. Kikuchi, S. Nishimura, M. Nagao, et al., Survey on the use of non-ceramic composite insulators, IEEE Trans. Dielectr. Electr. Insul. 6 (5) (1999) 548–556. [11] Z. Xu, S. Zhao, P. Guo, A portable NMR sensor used for assessing the aging status of silicone rubber insulator, Appl. Magn. Reson. 44 (12) (2013) 1405–1417. [12] G.H. Vaillancourt, S. Carignan, C. Jean, Experience with the detection of faulty composite insulators on high-voltage power lines by the electric field measurement method, IEEE Trans. Power Deliv. 13 (2) (1998) 661–666. [13] J.L. Fierro-Chavez, I. Ramirez-Vazquez, G. Montoya-Tena, On-line leakage current monitoring of 400 kV insulator strings in polluted areas, Generation Transmission and Distribution, IEE Proceedings-IET 143 (6) (1996) 560–564. [14] G.H. Vaillancourt, M. Hamel, J. Frate, Experience with two faulty composite insulators detection methods in Hydro-Quebec, 10th International Symposium on High Voltage Engineering 2 (4) (1997) 109–113. [15] Y.C. Chen, C.R. Li, X. Liang, et al., The influence of water and pollution on diagnosing defective composite insulator by electric field mapping, High Voltage Engineering, Eleventh International Symposium on (Conf Publ. No. 467) IET 4 (1999) 345–348. 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Bowler, Analysis of a concentric coplanar capacitive sensor for nondestructive evaluation of multi-layered dielectric structures, IEEE Trans. Dielectr. Electr. Insul. 17 (4) (2010) 1307–1318. [22] T. Chen, N. Bowler, A capacitive probe for quantitative nondestructive evaluation of wiring insulation, NDT E Int. 52 (2012) 9–15. [23] R.H. Bhuiyan, R.A. Dougal, M. Ali, Proximity coupled interdigitated sensors to detect insulation damage in power system cables, IEEE Sens. J. 7 (12) (2007) 1589–1596. [24] Robert T. Sheldon, Nicola Bowler, An interdigital capacitive sensor for nondestructive evaluation of wire insulation, IEEE Sens. J. 14 (4) (2014) 961–970. [25] Z. Chen, R.C. Luo, Design and implementation of capacitive proximity sensor using microelectromechanical systems technology, IEEE Trans. Ind. Electron. 45 (6) (1998) 886–894. [26] X.B. Li, S.D. Larson, A.S. Zyuzin, et al., Design principles for multichannel fringing electric field sensors, IEEE Sens. J. 6 (2) (2006) 434–440. [27] Almudena Rivadeneyraa, José Fernández-Salmeróna, Manuel Agudo-Acemelb, et al., Printed electrodes structures as capacitive humidity sensors: a comparison, Sens. Actuator A: Phys. 244 (2016) 56–65. [28] A. Rivadeneyra, J. Fernández-Salmerón, J. Banqueri, et al., A novel electrode structure compared with interdigitated electrodes as capacitive sensor, Sens. Actuators B 204 (2014) 552–560. [29] J.H. Kim, B.M. Moon, S.M. Hong, Capacitive humidity sensors based on a newly designed interdigitated electrode structure, Microsyst. Technol. 18 (1) (2012) 31–35. [30] A.R.M. Syaifudin, S.C. Mukhopadhyay, P.L. Yu, Electromagnetic field computation using COMSOL Multiphysics to evaluate the performance of novel interdigital sensors, in: Applied Electromagnetics Conference (AEMC), 2009, IEEE, 2009, pp. 1–4.
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[31] A.R.M. Syaifudin, S.C. Mukhopadhyay, P.L. Yu, et al., Detection of bacterial endotoxin in food: new planar interdigital sensors based approach, J. Food Eng. 114 (3) (2013) 346–360. [32] Li Nan, Guo Baolong, Wang Pai Proximity capacitive sensor design in an automatic car wiper control system, J. Mech. Eng. 46 (14) (2010) 12–17. [33] Zhou Yiyang, Tu Youping, Liu Dinghua, Chen Jingjing, Wang Cong Aging characteristic at different depths in a single composite insulators shed, IEEE Trans. Dielectr. Electr. Insul. 22 (3) (2015) 1630–1635.
Wu Bin received his B.S., M.S. and Ph.D. degree in 1984, 1990 and 1996 from Tianjin University, Beijing University of Aeronautics and Astronautics and Taiyuan University of Technology respectively. He is currently a professor in Beijing University of Technology. His main research interests include experimental solid mechanics, modern measurement and control technology, nondestructive testing of new technology, and new sensor technology.
Biographies
Jiao Jingpin was born in 1973 in HeBei (China). She received the BS degrees in Mechanical Engineering in 1998 in Yanshan University, and the PhD degree in 2005 from Beijing University of Technology, China. She is currently full professor at Beijing University of Technology in College of Mechanical Engineering and Applied Electronics Technology. Her main research interests include nondestructive testing of new technology, experimental solid mechanics, modern measurement and control technology, and new sensor technology.
Li Liang received his B.S. degree in 2013 from Qingdao University. He is currently a graduate student in Beijing University of Technology. His main research interests include non-destructive testing and automatic control.
He Cunfu received his B.S., M.S. and Ph.D. degree in1985, 1990 and 1996 from Taiyuan University of Technology, Huazhong University of Science and Technology and Tsinghua University respectively. He is currently a professor in Beijing University of Technology. His main research interests include mechanical testing theory method and technology, ultrasonic nondestructive testing technology, and sensor technology.
Contents lists available at ScienceDirect
Sensors and Actuators A: Physical journal homepage: www.elsevier.com/locate/sna
Novel capacitive proximity sensors for assessing the aging of composite insulators Jingpin Jiao ∗ , Liang Li, Bin Wu, Cunfu He College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China
a r t i c l e
i n f o
Article history: Received 2 September 2016 Received in revised form 31 October 2016 Accepted 18 November 2016 Available online 21 November 2016 Keywords: Composite insulator Capacitive proximity sensor Penetration depth Aging Non-destructive testing Silicone rubber sheds
a b s t r a c t A novel electrode structure consisting of a variable spacing interdigital electrode (VS-IDE) was proposed for assessing of the aging of silicone rubber sheds with variable thickness. A series of numerical simulations and experiments have been carried out to investigate the influences of finger number, unit width, and metallization ratio on the signal strength and penetration depth of sensors with a traditional interdigital electrode structure. According to the relationship between the penetration depth and the unit width, the width of each finger that composed the VS-IDE structure sensor was optimized individually to confine the electric field line within the sheds under test. Experimental results showed that compared to the other sensors, the optimal sensor exhibited high amplitude, high sensitivity, and excellent stability against the effects of environmental humidity. The developed capacitive proximity sensors have been used for assessing of the aging of silicone rubber sheds in composite insulators, and the feasibility of assessing insulation degradation by quantitative capacitive techniques is demonstrated. © 2016 Elsevier B.V. All rights reserved.
1. Introduction In recent years, composite insulators (silicone rubber insulators) have been widely used in power transmission systems because of their excellent attributes, such as being lightweight and high in mechanical strength, and offering excellent resistance to pollution and vandalism. However, the superior performance of composite insulators degrades over time because of high-voltage surge and unfavorable environmental factors, such as high temperatures, pollution, humidity, ultraviolet (UV) radiation, and oxidation. Aging of the composite insulators will lead to electrical property degradation or deterioration of the external insulation, threatening the safety and reliability of the power supply. A composite insulator consists of a glass fiber-reinforced polymer rod attached with metal end fittings and silicone rubber sheds which cover the rod (as shown in Fig. 1). The silicone rubber sheds are molded into a series of concentric disks to protect the rod from the environment and provide a sufficiently long leakage current path. Because of lengthy direct exposure to a harsh environment, aging is more likely to occur in silicone rubber sheds. It has been reported that the failures due to the aging of silicone rubber sheds in composite insulators have always been a challenge in engineer-
∗ Corresponding author. E-mail address: [email protected] (J. Jiao). http://dx.doi.org/10.1016/j.sna.2016.11.025 0924-4247/© 2016 Elsevier B.V. All rights reserved.
ing practice [1,2]. Therefore, it is critically important to detect the deterioration of silicone rubber sheds. Several methods have been proposed to estimate the aging of silicone rubber insulators [2,3]. These methods include visual inspection [4], UV imaging method [5,6], infrared ray imaging [7], ultrasonic non-destructive testing [8,9], hydrophobicity classification [10], nuclear magnetic resonance (NMR) [11], electric field measurement method [12], and leakage current measurement [13]. Extensive research has been conducted on assessment of aging of insulators using above methods; however, it has been found that these methods have limitations in measurement precision, reliability, and engineering practicality [14,15]. For capacitive sensing techniques the most common electrode structures are the planar parallel plate electrodes and the co-planar electrodes (called capacitive proximity sensors). The working principle of capacitive proximity sensors are based on the fringing effect of the electric field. Compared to the traditional parallelplate capacitor, capacitive proximity sensors have unique features, such as one-side access (the other side can be open to the ambient), easy control of signal strength by changing its dimensions, multiple physical effects in the same structure (electric, magnetic, acoustic), and a wide frequency spectrum of use. Therefore, they have been widely used in many fields, such as material property monitoring, humidity sensing, electrical insulation properties sensing, chemical sensing, and bio-sensing.
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Fig. 1. Structure of composite insulator. Fig. 3. Fundamental parameters of interdigitated electrode structure.
Fig. 2. 3D model of the composite insulator and the cross-sectional drawing of silicone rubber shed.
Capacitive proximity sensing techniques have been widely used for nondestructive evaluation (NDE) of low-conductivity materials [16–21]. Based on detecting the local variation of the dielectric properties of materials under testing, capacitive sensing techniques have been used for structure-healthy monitoring (SHM) of the concrete slab retrofitted with composites [18,19]. EI-Dakhakhn et al. [20] applied the proximity capacitive technique for unfilled cells detection in grouted masonry constructions. A concentric coplanar capacitive sensor was developed for the quantitative characterization of material properties for multi-layered dielectrics [21], and the effectiveness of the proposed method for water intrusion detection in random structures was experimentally validated. The outside insulation layer of the electric cables is also typically low-conductivity material. Research has applied capacitive sensing techniques to characterize cable insulation properties. Chen and Bowler [22] designed a capacitive probe for evaluation of wiring insulation permittivity, and experiments demonstrated the feasibility of assessing wiring insulation degradation status by quantitative capacitive techniques. Proximity-coupled interdigital sensors are introduced to detect insulation damage in power system cables, and the measurement results confirm that the proximity capacitive technique is sensitive to the presence of holes and water trees in a power line cable [23]. To detect aircraft wire aging damage, Sheldon and Bowler [24] developed an interdigital capacitive sensor and experimentally verified the capacitance variation resulted from aircraft fluid immersion. Research indicates that the patterns and parameters of electrodes have great influence on capacitive sensor performances, such as signal strength, penetration depth, sensitivity, and noise-tosignal ratio, all of which affect the detecting capability of capacitive proximity sensors. Many efforts have been devoted to improving the performance of capacitive proximity sensors [25–27]. Several sensor patterns including square-shaped, maze, spiral, and comb patterns were investigated, and it was demonstrated that complex sensor patterns can increase the effective electrode area and then improve sensor signal and sensitivity [25]. To improve signal strength and sensitivity, Rivadeneyra et al. [28] designed a serpentine structure which is a combination of meandering and interdigitated electrodes. A capacitive sensor of interdigital elec-
Fig. 4. 2D finite element model of proximity interdigital sensor.
trode structure with increased height was fabricated for humidity measurement [29]. Compared to the traditional interdigital electrode sensor, the proposed sensor showed higher sensitivity owe to the horizontal electric field lines confined in the polyimide sensing layer. Syaifudin et al. [30,31] investigated the influence of electrode configuration on performance of capacitive proximity sensors and found that the optimal number of negative electrodes between two adjacent positive electrodes can improve the sensitivity for chemical detection. For water detection in an automatic windshield system, a few petal-like electrode structures were designed [32]. The silicone rubber sheds are made of high-temperature vulcanization silicone rubber (HTVSR), a typical dielectric material [33]. Aged silicone rubber may lead to fracture of the molecular chains and produce large numbers of free radicals, changing the permittivity (dielectric constant). Capacitive sensing, however, is ideally suited for characterization of dielectric materials due to the closely relationship between the measured capacitance and the relative permittivity (dielectric constant) of the material. To ensure the self-cleaning ability of the composite insulators under contaminated conditions, the umbrella skirt structure is designed to be an inclined plane with a certain angle, whose thickness decreases gradually from near the fiberglass-reinforced resin rod to the edge of the umbrella skirt. In this paper, the capacitive proximity sensing method is applied to assess the insulation degradation of silicone rubber sheds in a composite insulator. The influence of finger number, unit width, and metallization ratio on the performance of capacitive proximity sensors was investigated by simulation and experiments. Capacitive proximity sensors with variable spacing interdigital electrode (VS-IDE) structure were designed for nondestructive testing of thickness gradient samples. The proposed sensors are experimentally measured and used to assess the aging of silicone rubber sheds in a composite insulator.
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η=0.1 η=0.2 η=0.3 η=0.4 η=0.5 η=0.6 η=0.7 η=0.8 η=0.9
5 Capacitance C/ F
60
x 10
4 3 2 1
40 30 20 10 0
0
2
η=0.1 η=0.2 η=0.3 η=0.4 η=0.5 η=0.6 η=0.7 η=0.8 η=0.9
50 Relative capacitance /%
6
77
2
4
4 6 8 10 12 14 Thickness of test samples h/mm (a) Absolute capacitance
6 8 10 12 14 Thickness of test samples h/ mm (b) Relative capacitance
Fig. 5. Capacitance obtained from simulations when the finger number of sensor is 4.
2. Capacitive sensor design and optimization Fig. 2 shows the 3D model of the detected composite insulator, FXBW4-110/100-B, and the cross-sectional drawing of silicone rubber shed (umbrella skirt). The outer and inner radii of the umbrella skirt are 59 mm and 13 mm, respectively. The thickness of umbrella skirt decreases gradually from 6.27 mm near the core rode to 2.33 mm at the outer edge. The angle of the top and bottom surfaces is about 5◦ . For the convenience of sensor installation, a limited region near the core rode and at the outer edge is reserved. Consequently, 38 mm in the radial direction can be used for the arrangement of electrodes. In this region, the thickness of umbrella skirt decreases gradually from 5.89 to 2.0 mm. Owing to the high signal strength and sensitivity, the interdigitated electrode structure has been widely used in capacitive proximity sensing. The fundamental parameters of interdigitated electrode structure are illustrated in Fig. 3, including mainly the number of fingers n, unit width of each finger w, and spacing between two adjacent fingers g. Here, a new parameter C, named width of a basic interdigital unit, is defined. Obviously, the value of C equals the sum of finger width w and finger spacing g. Likewise, the metallization ratio Á is equal to the ratio of the finger width w to the basic interdigital unit width C, = w/(w + g). L is the length of the interdigitated electrode structure, which is specified as 38 mm in this paper. 2.1. Numerical simulation of proximity interdigital sensors The effect of the electrode parameters (finger number, metallization ratio) on the performance of proximity interdigital sensors was investigated by numerical simulations. An FEM (finite element method) numerical model of the proximity interdigital sensor was developed, and electrostatic simulations were performed in Comsol Multiphysics 4.4 software. Fig. 4 shows a typical 2D finite element model of proximity interdigital sensor with 4 fingers, consisting of driving electrodes, sensing electrodes, substrate for supporting the electrodes, shielding layer, and the materials under test. The surrounding of model is full of air. The test sample is high-temperature vulcanized silicone rubber (HTVSR) with relative dielectric permittivity 5.6, and the substrate is polymethyl methacrylate with a thickness of 2.5 mm and relative dielectric permittivity of 4.2. The thickness of the copper electrode is 0.1 mm. The driving electrode is set to 5 V and all other electrodes are set to 0 V, a Dirichlet boundary condition in nature. Based on the above model, simulations were first performed to investigate the effect of the metallization ratio on the measured capacitance at samples with different thickness. In these
simulations, the metallization ratio varies from 0.1 to 0.9 with an increment of 0.1; and the thickness of test samples varies from 2 to 15 mm with an increment of 1 mm. In this section the length of the electrode structure is constant (38 mm). According to the geometric relations of interdigitated electrode structure, the finger width and spacing in each model can be determined as follows: w=
∗L n
(1)
g=
(1 − ) ∗ L n−1
(2)
According to the simulated result, the inter-electrode capacitance can be calculated using C=
1 1 Dd˝ = ε0 εr ∇ ˚d˝, V˝ V˝
(3)
where is the electrode-covered area in models, D is the electric displacement vector, and V is the potential difference between the driving and sensing electrodes. Fig. 5(a) shows the capacitance values obtained from the simulations when the finger number is 4. It can be seen that the metallization ratio and thickness of test sample affects the measured capacitance value. When the thickness of test samples is identical, the capacitance values increase with the increasing of the metallization ratio; moreover, the capacitance values from different metallization ratios exhibit similar trends with respect to the thickness of test samples. That is, the capacitance increases slightly in proportion to the thickness of test samples and then reaches certain stable values. One explanation for this is that along with the increase of metallization ratio comes an increase in effective area of electrodes, which lead to the increasing the capacitance with metallization ratio; as the thickness of test samples becomes thicker, more electric field lines pass through the test samples and reach the sensing electrodes, which lead to an increase in capacitance values. However, the capacitance will be stabilized at certain values once the thickness of the test sample reaches the specific penetration depths. Penetration depth is a measure of evaluating the ability of electric field intensity penetrating through the test samples. Until now, no strict definition of penetration depth for capacitive proximity sensors has existed. One way to evaluate the penetration depth is according to the distribution of the relative capacitance ıC, which can be represented as ıC =
|C − Cs | × 100%, Cs
(4)
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Fig. 6. Distribution of electric field lines when metallization ratio varied from 0.1 to 0.9, respectively.
where Cs is the stable capacitance at the same metallization ratio. The effective penetration depth corresponds to the position where the relative capacitance equals 10%. The relative capacitance and penetration depth corresponding to Fig. 5(a) are shown in Fig. 5(b). It can be seen that the penetration depth decreases as the metallization ratio increases. A possible explanation is that the increasing of metallization ratio results in a decreasing of finger spacing, which is closely related to the penetration depth. The effect of metallization ratio on penetration depth can also be vividly illustrated by the distribution of the electric field in space. Fig. 6 shows the distribution of electric field lines when the metallization ratio of electrodes varies from 0.1 to 0.9, the finger number is 4, and the thickness of samples is identical. It can be seen that with the increase of metallization ratio, there were less electric field lines which can penetrate the test samples and escape to the air. Though the distribution of electric field lines cannot use for quantitative description of penetration depth, the results support above conclusions that along with the increase of metallization ratios comes a decrease in penetration depths and an increase in capacitance value. Similarly, numerical simulation analysis was carried out for the influence of metallization ratio on the performance of proximity interdigital sensors with different number of fingers. According to the numerical simulation, the dependencies of the penetration depth versus the metallization ratio for proximity interdigital sensors with different number of fingers are depicted in Fig. 7. The finger number and metallization ratio obviously greatly affect the penetration depth of proximity interdigital sensors. Along with the increase of finger number comes an obvious decrease in penetration depth. For proximity interdigital sensors with identical finger number, the penetration depth decreases with the increasing of metallization ratio, which is consistent with above results.
Fig. 7. Penetration depth versus metallization ratio for proximity interdigital sensors with different number of fingers.
The penetration depth curves shown in Fig. 7 are particularly useful for the structure parameter in designing of proximity interdigital sensors. According to the thickness distribution range of the umbrella skirt (2–5.89 mm), the basic parameters of proximity interdigital sensors, such as finger number, width of basic interdigital unit, and metallization ratio, can be determined. The penetration depth may reach up to 6 mm when the metallization ratio is less than 0.4 for proximity interdigital sensors with 4 fingers. At this case the width of a basic interdigital unit C is 9.5 mm; the penetration depth may reach up to 2 mm when the metallization ratio is less than 0.5 for proximity interdigital sensors with 8 fingers. In this case the width of a basic interdigital unit C is 4.75 mm. Therefore,
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45
C10-η0.5 C9-η0.5 C8-η0.5 C7-η0.5 C6-η0.5 C5-η0.5 C4-η0.5
Relative capacitance d /%
40 35 30 25 20 15 10 5 Fig. 8. 2D simulation model for proximity interdigital sensors with single unit.
0 x 10
2
-12
1.4
6 8 10 12 14 Thickness of test samples
Fig. 10. Relative capacitance value versus thickness of test samples for proximity interdigital sensor with single unit.
1.3 Capacitance /F
4
1.2 1.1 C10-η0.5 C9-η0.5 C8-η0.5 C7-η0.5 C6-η0.5 C5-η0.5 C4-η0.5
1 0.9 0.8 0.7 2
4
6
8
10
12
14
Thickness of test samples h/mm Fig. 9. Capacitance value versus thickness of test samples for proximity interdigital sensor with single unit.
in following research, the width of a basic interdigital unit ranges from 4 to 10 mm. 2.2. Numerical simulation of proximity interdigital sensors with single unit A 2D numerical simulation model was established as shown in Fig. 8, and simulations were carried on proximity interdigital sensors with a single unit, in which the width of a basic interdigital unit ranged from 4 to 10 mm. The influences of basic interdigital unit width and test sample thickness on the performance of proximity interdigital sensors with a single unit were investigated through simulation. In simulation models, the metallization ratio was set to 0.5, and the other parameters were the same as those described in Section 2.1. Figs. 9 and 10 give the results of the simulations. It can be seen that the variations of capacitance and its relative value with thickness of test samples closely resemble that obtained from sensors with multiple fingers (as shown in Fig. 5). In addition, as can be seen from the capacitance values in Fig. 9, the width of the basic interdigital unit greatly affects the measured capacitance value. When the thickness of test samples is identical, the capacitance values decrease with the increasing of width of a basic interdigital unit. However, as seen from Fig. 10, for interdigital sensors with a single unit the penetration depth increases with the increasing of unit width. Similarly, numerical simulation was carried out for the influence of unit width on the performance of proximity interdigital
Fig. 11. Penetration depth versus metallization ratio for proximity interdigital sensors with different unit width.
sensors with different metallization ratio. According to the results of numerical simulation, the dependencies of the penetration depth versus the metallization ratio for proximity interdigital sensors with different unit width are depicted in Fig. 11. As expected, unit width and metallization ratio obviously greatly affect the penetration depth of proximity interdigital sensors. Along with the increase of unit width comes an obvious increase in penetration depth. An explanation for this is that along with the increase of unit width (metallization ratio is constant) comes an increase in effective area of electrodes, which lead to the increasing of capacitance values with unit width. Meanwhile, the variations of penetration depth versus metallization ratio exhibited similar behavior for proximity interdigital sensors with different unit width. When the metallization ratio is less than 0.4, the penetration depth slowly increases with metallization ratio; when the metallization ratio is within the range of 0.4–0.7, the penetration depth is almost constant; and when the metallization ratio is greater than 0.7, the penetration depth slowly decreases with metallization ratio. The finger number and metallization ratio obviously greatly affect the penetration depth of proximity interdigital sensors. Along with the increase of finger number comes an obvious decrease in penetration depth. For proximity interdigital sensors with identical finger number, the penetration depth decreases with the increasing of metallization ratio, which is consistent with above results.
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Table 1 Parameters for different proximity interdigital capacitive sensors (unit: mm). Sensor Number
Interdigital unit C1
Sensor-1# Sensor-2# Sensor-3# Sensor-4#
C2
C3
C4
C5
C6
w1
g1
w2
g2
w3
g3
w4
g4
w5
g5
w6
3.8 5 6 7
7.6 5 4 3
3.8 5 5 5.6
7.6 4 3.2 2.4
3.8 4 4.8 4.9
7.6 3 2.4 2.1
3.8 3 3.6 4.2
– 2.5 2 1.8
– 2.5 3 3.5
– 2 1.6 1.5
– 2 2.4 2
Fig. 12. Schematic diagram of VS-IDE capacitive sensor. Fig. 13. Electrode arrangement of VS-IDE capacitive sensor.
The relationship of penetration depth and metallization ratio under different unit width provides guidelines for the design of proximity interdigital sensors used in test samples with different thickness.
Table 2 Comparison of the capacitance for different sensors at different environmental humidity. Capacitance (pF)
2.3. Optimization of proximity interdigital sensors Considering the gradually varying thickness of silicone rubber sheds, the width and metallization ratio of each interdigital unit composed of proximity interdigital sensors were optimized individually. The optimization was to obtain high amplitude and high sensitivity under the condition that the penetration depth was ensured. In pursuance of the above guidelines, a novel capacitive proximity interdigital sensor consisting of VS-IDE structure has been developed for nondestructive testing of silicone rubber sheds with gradually varying thickness. Fig. 12 shows the schematic diagram of a VS-IDE capacitive sensor, which consists of driving electrode (1), sensing electrode (2), substrate (3), guarding electrode (4), and lead connector (5). The driving electrode and the sensing electrode are deposited on a PMMA (polymethyl methacrylate) substrate, while the guarding electrode is deposited on the opposite side of the substrate to protect the sensor. The lead connector is welded on the guarding plane to provide a reliable connect for the sensor and experimental equipment. The middle pins of the SMB connectors are respectively connected to the driving electrode and the sensing electrode through the pre-reserved holes on the substrate. Both the driving and sensing electrodes consist of several interdigital fingers, which are arranged alternately in sequence, and the width and metallization ratio for each interdigital unit is determined by the local thickness of the test sample. The arrangement of electrodes is shown in Fig. 13. As mentioned in Section 2, in the radial direction of the umbrella skirt the width that can be used for the arrangement of electrodes is 38 mm, and thickness ranges from 5.89 to 2.0 mm. In accordance with the requirement of penetration depth shown in Fig. 11, only the interdigital units, whose width is 10 mm, and the metallization ratio (0.5, 0.6, or 0.7) satisfied the penetration depth criteria of 5.83 mm. Therefore, 3 VS-IDE capacitive sensors are obtained on condition that the total width of the electrode is identical. Table 2
no water film 0.5-mm thick water film capacitance variation relative capacitance change rate
Sensor number 1#
2#
3#
4#
1.047 1.560 0.513 48.95%
4.151 4.641 0.490 11.81%
4.919 5.427 0.507 10.31%
5.875 6.433 0.5688 9.51%
Fig. 14. Finite element model for designed sensors.
provides details of the capacitive sensors, including a traditional proximity interdigital sensor with 4 fingers. Since it has an equal spacing interdigital electrode, it is named ES-IDE capacitive sensor (Sensor-1#). Similarly, performance of 4 sensors was studied with numerical simulations. Fig. 14 shows the finite element model for the designed sensors. Fig. 15 shows the electric field line distribution of the sensors. Compared to the distribution of electric field lines for the ES-IDE capacitive sensor, the electric field lines of VS-IDE capacitive sensors are mostly confined within the test samples. In particular, the electric field lines are further confined in the test sample for sensor4#. The capacitance value of 4 sensors are, respectively, 1.05pF, 4.15pF, 5.12pF, and 5.87pF. Fig. 16 shows the capacitance value versus relative dielectric constant of the test sample. It can be seen that compared to the ES-IDE capacitive sensor, the proposed VS-IDE capacitive sensors perform better in signal amplitude and mea-
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Fig. 15. Electric field line distribution for different sensors: (a) Sensor-1#, (b) Sensor-2#, (c) Sensor-3#, (d) Sensor-4#.
Capacitance /F
-12
9 8 7 6 5 4 3 2 1 0
x 10
Fig. 17. Schematic of experimental system for capacitance measurement.
1# 2# 3# 4#
2
3
4
5
6
7
8
Relative dielectric constant Fig. 16. Capacitance value versus relative dielectric constant of test samples using different sensors.
surement sensitivity. Furthermore, compared to the other 2 VS-IDE capacitive sensors, sensor-4# has optimal performance. Another advantage of the proposed VS-IDE capacitive sensors is that they are less affected by environmental factors, such as humidity. To investigate the effect of environmental humidity on the performance of the above sensors, a thin layer of water with thickness of 0.5 mm was introduced in the simulation model shown in Fig. 14. Table 2 shows the simulated results and capacitance variations due to the presence of the water layer. The water layer has different effect on the capacitance of different sensors. It has a significant effect on the capacitance of ES-IDE capacitive sensor, and its relative change rate of capacitance is nearly 48.95%; however, it has a slight effect on the capacitance of VS-IDE capacitive sensors. In particular, it has minimal influence on the performance of sensor-4#. Therefore, simulation demonstrates that the proposed VS-IDE capacitive sensors exhibited excellent performance in signal amplitude, sensitivity, and stability against the effects of environmental humidity. 3. Performance testing of capacitive proximity sensors Benchmark capacitive experiments were carried out to test the performance of the capacitive proximity sensors. The schematic of experimental system is shown in Fig. 17. 4294A Precision Impedance Analyzer (Agilent) is the core component of the capacitive measurement system. The test samples are made of HTVSR, and their geometry is identical to those in the simulations above. A special jig is used to keep contact tight between the capacitive sensor and the test sample. Fig. 18 shows the measured capacitance of the proximity interdigital capacitive sensors described in Table 1. It is noted that the experimental and simulation results of different proximity
Fig. 18. Measured capacitance of the proximity interdigital capacitive sensors.
Table 3 Comparison of the measured capacitance for different sensors at different environmental humidity. Capacitance (pF)
no water film with water film capacitance variation relative capacitance change (%)
Sensor number 1#
2#
3#
4#
1.411 1.560 0.149 10.53
3.340 3.432 0.092 2.75
3.894 3.952 0.045 1.48
4.579 4.602 0.016 0.51
interdigital capacitive sensors have essentially the same changing tendency. Experiments demonstrate that compared to the ES-IDE capacitive sensor, the proposed VS-IDE capacitive sensors have a better performance in signal amplitude. Additionally, experiments were conducted to verify the environmental stability of the VS-IDE capacitive sensors. In these experiments a thin layer of water was coated on the test samples; the other arrangement was identical to experiments above. Table 3 compares the measured capacitance for different sensors at different environmental humidity. Clearly, the experimental results agree with the above simulation results. Experiments demonstrate that the water layer has a slight effect on the capacitance of VSIDE capacitive sensors. The relative capacitance variation ratio of sensor-4# is the lowest at only 0.51%. In summary, experiments demonstrate that the proposed VSIDE capacitive sensors exhibited excellent performance in signal amplitude, sensitivity, and stability against the effects of environmental humidity. Besides, among 3 kinds of VS-IDE capacitive sensors, the performance of sensor #4 is the best one.
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-11
1.2
x 10
Capacitance C / F
0h
1
10h 20h
0.8
40h 60h
0.6 0.4 0.2 0 1#
2# 3# Sensor number
4#
Fig. 19. Annular capacitive proximity sensors. Fig. 22. Measured capacitance from umbrella sheds with varying degrees of aging.
in Table 1. The sensors were fabricated using printed circuit board technology as shown in Fig. 19. Fig. 20 shows the experimental system for the aging detection of silicone rubber sheds. Similar to the rectangle jig in Fig. 17, an annular jig keeps contact tight between the capacitive sensor and the sheds. 4294A Precision Impedance Analyzer (Agilent) is used for capacitance measurement. The tested composite insulators, FXBW4-110/100-B, were soaked in sulfuric acid (concentration of 70%) at different immersion periods to accelerate different degrees of aging. Fig. 21 shows the typical unaged and aged umbrella sheds. A thin layer of age coating can be seen to have formed on the surface of the aged shed layer, which exhibits the phenomenon of chalking and whitening. In addition, visible micro-cracks appear on the surface when the shed is bent slightly. 4.2. Results and discussion Fig. 20. Experimental setup for aging detection of silicone rubber sheds.
4. Experiments of aging detection of silicone rubber sheds In this section, the capacitive proximity sensing method is applied to assess the insulation degradation of silicone rubber sheds in a composite insulator. 4.1. Experimental system Four kinds of annular capacitive proximity sensors were designed for the aging detection of silicone rubber sheds (shown in Fig. 1). The structural parameters of sensors, such as finger number, unit width, and metallization ratio, are identical with those
Experiments of capacitance measurement were conducted on umbrella sheds with varying degrees of aging using the designed annular capacitive proximity sensors. Fig. 22 shows the typical results. For each case, the experiment was repeated 6 times, and the error bars represent the standard deviation of these measurements. The measured capacitance values can be seen to have decreased with the increase of the immersion period for the same sensor, and the capacitance measured by the VS-IDE capacitive sensors is significantly higher than that of the ES-IDE capacitive sensor. Among 3 VS-IDE capacitive sensors, sensor-4# performs best in signal amplitude in any case. Fig. 23 gives the measured capacitance variations versus the immersion period. The immersion period obviously greatly affects the measured capacitance value, and the capacitance variations from different sensors exhibit similar trends with respect to the
Fig. 21. Comparison of the different test specimen.
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-12
Capacitance variation C / F
2
x 10
1.5
1
Sensor-1# Sensor-2# Sensor-3# Sensor-4#
0.5 0
10
20
30 40 50 Immersion time t/ h
60
Fig. 23. Measured capacitance variation versus immersion period.
immersion period. That is, the capacitance variation increases slightly in proportion to the immersion period and then reaches certain stable values. Additionally, under the same immersion period, the capacitance variation measured by the annular VSIDE capacitive sensors was significantly higher than that of the ES-IDE capacitive sensor. Among the 3 VS-IDE capacitive sensors, sensor-4# has the highest measurement sensitivity. Therefore, the capacitive proximity sensing method can be used for evaluation of the aging of the umbrella shed in composite insulators, and the VS-IDE capacitive sensor is more sensitive to the aging of umbrella sheds. 5. Conclusion The potential of the capacitive proximity sensing technique for the aging detection of umbrella shed in composite insulators was investigated. Numerical simulations have been carried out to analyze the influences of finger number, unit width, and metallization ratio on the signal strength and penetration depth of sensors with traditional interdigital electrode structure. Considering the gradually varying thickness of silicone rubber sheds, the width and metallization ratio of each interdigital unit composed of the proximity interdigital sensors were optimized individually to confine the electric field line within the sheds being tested. A novel electrode structure consisting of a VS-IDE was proposed for assessing of the aging of silicone rubber sheds with variable thickness. Experiments demonstrated that the proposed VS-IDE capacitive sensors exhibited excellent performance in signal amplitude, sensitivity, and stability against the effects of environmental humidity. The developed capacitive proximity sensors have been used for assessing of the aging of silicone rubber sheds in composite insulators. Experimental results demonstrated that the capacitive proximity sensing method can quantitatively evaluate the aging of umbrella shed in composite insulators, and compared to the ES-IDE capacitive sensor the VS-IDE capacitive sensor is more sensitive to aging of umbrella sheds. Acknowledgements The study was supported by the National Natural Science Foundation of China (Grant nos. 11272017, 11572010); the National Key Research and Development Program of China (2016YFF0203002). References [1] N. Yoshimura, S. Kumagai, S. Nishimura, Electrical environmental aging of silicone rubber used in outdoor insulation, IEEE Trans. Dielectr. Electr. Insul. 6 (5) (1999) 632–650.
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Wu Bin received his B.S., M.S. and Ph.D. degree in 1984, 1990 and 1996 from Tianjin University, Beijing University of Aeronautics and Astronautics and Taiyuan University of Technology respectively. He is currently a professor in Beijing University of Technology. His main research interests include experimental solid mechanics, modern measurement and control technology, nondestructive testing of new technology, and new sensor technology.
Biographies
Jiao Jingpin was born in 1973 in HeBei (China). She received the BS degrees in Mechanical Engineering in 1998 in Yanshan University, and the PhD degree in 2005 from Beijing University of Technology, China. She is currently full professor at Beijing University of Technology in College of Mechanical Engineering and Applied Electronics Technology. Her main research interests include nondestructive testing of new technology, experimental solid mechanics, modern measurement and control technology, and new sensor technology.
Li Liang received his B.S. degree in 2013 from Qingdao University. He is currently a graduate student in Beijing University of Technology. His main research interests include non-destructive testing and automatic control.
He Cunfu received his B.S., M.S. and Ph.D. degree in1985, 1990 and 1996 from Taiyuan University of Technology, Huazhong University of Science and Technology and Tsinghua University respectively. He is currently a professor in Beijing University of Technology. His main research interests include mechanical testing theory method and technology, ultrasonic nondestructive testing technology, and sensor technology.